网络动力学中伪稳定态的出现
The emergence of pseudo-stable states in network dynamics
摘要：
在网络动力学的背景下，系统的复杂性增加了可能的进化路径，而这些路径往往是不确定的。偶尔，随着时间的推移会形成一些地图路径，将系统引导到某些特定的状态。这项研究的主要目的是发现一个指标，可以帮助预测这些伪确定性路径提前。在这里，我们研究的动态网络的基础上海德平衡理论，国家的趋势，系统朝着减少紧张。这种倾向导致系统的一些局部和整体的最小张力状态称为“堵塞状态”和“平衡状态”，分别。我们发现，不仅对堵塞状态的路径是不完全随机的，但也存在秘密的伪确定性路径，约束系统最终在这些特殊的状态。研究结果表明，逆参与比方法（IPR）可以作为一个合适的指标，显示系统的集体行为。根据这种方法，这些特定路径是系统中参与最多的路径。在距离和朝向局部最小值的可选择路径之间存在直接的比例关系;其中，通过接近最终步骤，除了到达堵塞状态的路径之外，没有其他路径。
英文摘要：
In the context of network dynamics, the complexity of systems increases possible evolutionary paths that often are not deterministic. Occasionally, some map routs form over the course of time which guide systems towards some particular states. The main intention of this study is to discover an indicator that can help predict these pseudo-deterministic paths in advance. Here we investigate the dynamics of networks based on Heider balance theory that states the tendency of systems towards decreasing tension. This inclination leads systems to some local and global minimum tension states called "jammed states" and "balanced states", respectively. We show that not only paths towards jammed states are not completely random but also there exist secret pseudo deterministic paths that bound the system to end up in these special states. Our results display that the Inverse Participation Ratio method (IPR) can be a suitable indicator that exhibits collective behaviors of systems. According to this method, these specific paths are those that host the most participation of the constituents in the system. A direct proportionality exists between the distance and the selectable paths towards local minimums; where by getting close to the final steps there is no other way but the one to the jammed states.
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